Goodwin Sara, Gade Alexandra M, Byrom Michelle, Herrera Baine, Spears Camille, Anslyn Eric V, Ellington Andrew D
Cold Spring Harbor Laboratory, Cold Spring Harbor, NY (USA).
Department of Chemistry A1590, The University of Texas at Austin, Austin, TX 78712 (USA).
Angew Chem Int Ed Engl. 2015 May 18;54(21):6339-42. doi: 10.1002/anie.201501822. Epub 2015 Mar 31.
Differential sensing (DS) methods traditionally use spatially arrayed receptors and optical signals to create score plots from multivariate data which classify individual analytes or complex mixtures. Herein, a new approach is described, in which nucleic acid sequences and sequence counts are used as the multivariate data without the necessity of a spatial array. To demonstrate this approach to DS, previously selected aptamers, identified from the literature, were used as semi-specific receptors, Next-Gen DNA sequencing was used to generate data, and cell line differentiation was the test-bed application. The study of a principal component analysis loading plot revealed cross-reactivity between the aptamers. The technique generates high-dimensionality score plots, and should be applicable to any mixture of complex and subtly different analytes for which nucleic acid-based receptors exist.
传统上，差分传感（DS）方法使用空间排列的受体和光信号从多变量数据创建得分图，以对单个分析物或复杂混合物进行分类。本文描述了一种新方法，其中核酸序列和序列计数被用作多变量数据，而无需空间阵列。为了证明这种DS方法，从文献中选择的先前鉴定的适体被用作半特异性受体，使用下一代DNA测序来生成数据，细胞系分化作为测试应用。对主成分分析载荷图的研究揭示了适体之间的交叉反应性。该技术生成高维得分图，并且应该适用于存在基于核酸的受体的任何复杂且细微不同的分析物混合物。
